The impact of digitalization on the economic growth of the European Union: an empirical study
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DOI: 10.15587/1729-4061.2024.304256
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- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- Rinaldo Evangelista & Paolo Guerrieri & Valentina Meliciani, 2014. "The economic impact of digital technologies in Europe," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(8), pages 802-824, November.
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
- Daniil Revenko & Yuri Romanenkov & Valentyna Hatylo & Vira Lebedchenko & Oleksandr Titarenko, 2023. "Improvement of the methodical approach to assessing the level of innovation potential of the countries of the European Union," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 1(13(121)), pages 63-73, February.
- Aurelija Burinskienė & Milena Seržantė, 2022. "Digitalisation as the Indicator of the Evidence of Sustainability in the European Union," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
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Keywords
digital transformation; economic growth; production function; statistical modeling; European Union;All these keywords.
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